Journal ArticleLearning-accelerated discovery of immune-tumour interactionsOzik, Jonathan; Collier, Nicholson; Heiland, Randy; An, Gary; Macklin, PaulWe present an integrated framework for enabling dynamic exploration of design spaces for cancer immunotherapies with detailed dynamical simulation models on high-performance computing resources. Our framework combines PhysiCell, an open source agent-based simulation platform for cancer and other multicellular systems, and EMEWS, an open source platform for extreme-scale model exploration. We build an agent-based model of immunosurveillance against heterogeneous tumours, which includes spatial dynamics of stochastic tumour–immune contact interactions. We implement active learning and genetic algorithms using high-performance computing workflows to adaptively sample the model parameter space and iteratively discover optimal cancer regression regions within biological and clinical constraints.2019-08-0510188156Molecular Systems Design & Engineering44747 to 7602058-9689https://doi.org/10.1039/c9me00036d1720625National Science Foundation